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aigon.ai / connecting-mcp

Quick Start

To connect Aigon to your LLM you need to add an MCP server to it. As an example we show here how to connect Aigon to Claude (details):

  1. Type and send the /weblogin (short /wl) command in WhatsApp to get a login link for your browser
  2. Open the login link in your main browser (copy and paste if need be), then click on the orange login button to log into Aigon (details)
  3. In your main browser, go to claude.ai, log into Claude if need be, and add in settings add the Aigon MCP server mcp.aigon.ai/sse as aigon-prod to your Claude workspace (details).
  4. The server will open an approval page on a1.aigon.ai where you will be asked to approve the connection. Click Approve and Redirect to complete the connection.
  5. You may also have to allow the domains mcp.aigon.ai and a1.aigon.ai in Claude's Capabilities tab if you are using Cowork (details).
  6. In Claude, ask it to explore the Aigon MCP server

For other LLMs, the steps are similar, provided they support MCP, or they are able to call a REST API (details). Point them to the page you are currently reading and have them explain to you how to best connect.

Logging into Aigon

If you want to use OAuth authentication your first have to log your browser into the aigon website at a1.aigon.ai. In most cases, the easiest way to do so is to log in using a login link that you generate using the /weblogin or /wl command.

The login link works in a two step process, first opening a page that says "Please click here to login" and you are only logged in once you click the button. The reason for this is that it allows you to transfer the login links, that can only be used once, to another browser or device. For example

QR code

There is a second method for logging into devices which is useful if you cannot get a link to them directly. Simply open

a1.aigon.ai

and scan the QR code that appear on this page on your phone. Provided you are logged into Aigon on your phone it will lead you to an approval page that will allow you to log into the computer without needing a login link.

Bearer token

If your LLM cannot do OAuth, a bearer token is the fallback — see Bearer token in the Appendix.

MCP for Claude

You can in principle add MCP servers locally, but this is not recommended. Firstly it means they are only available on the computer where they have been added, and secondly they need to reauthenticate every time the MCP server is restarted — which happens quite often, because it is under active development.

Instead we recommend installing the MCP server in claude.ai directly. First log into your normal claude.ai workspace and find the Customize menu point. When you click there you need to find the Connectors tab, then Add followed by Custom connector.

The Claude menu bar, with Customize The Connectors tab, with Add custom connector

Fill in a name and the server address:

aigon-prod / https://mcp.aigon.ai/sse

Leave the OAuth client ID and secret under Advanced settings empty — they are optional and Aigon does not need them.

When you click Add it will offer to connect. When you click that, the OAuth flow on a1.aigon.ai opens, provided you have previously logged in. Click Approve and Redirect, and the connection is established.

The Add custom connector dialog, filled in aigon-prod connected, with its tool permissions

Once connected you will see the server's tool permissions — Call, Help and Skill, plus Whoami. Those first three are the whole API; see the CaSH model below. Setting them to Always allow saves being asked on every call.

MCP for Cowork

Cowork is a separate surface inside the same Claude account, with its own tab in Settings. It shares the account's connectors: an Aigon connector added under MCP for Claude is the same connector here and does not need adding a second time.

What it does not share is the assumption that the network is open. Cowork works in a sandbox, and the sandbox reaches only the domains on its allowlist.

Domain allowlist

If Claude refuses the connection, or reports that it cannot reach mcp.aigon.ai, this is almost always the reason. Open Settings and select the Capabilities tab:

Claude Settings, Capabilities tab, showing the domain allowlist set to All domains

The setting shown there is All domains - "Claude can access all domains on the internet" - and with that every Aigon access point is reachable. If yours is narrowed to a specific list instead, add

mcp.aigon.ai

to it, and a1.aigon.ai as well if you want the OAuth flow to complete inside the sandbox rather than in your ordinary browser.

Note the trade-off the same screen warns about. The capability that makes the sandbox useful - code execution, file processing - is also what makes an open allowlist worth a second thought: a sandbox that can reach every domain can carry your data to every domain. Allowlisting the two Aigon hosts and nothing else is the tighter setting, and it is enough for everything in this guide.

The allowlist governs the sandbox, not the connector. MCP CURL runs inside the sandbox and is therefore subject to it; a connector added under Customize -> Connectors is brokered by Claude itself and is not.

MCP for ChatGPT

ChatGPT only allows connecting MCP servers on the expensive Pro subscription and above — and even there only with read and fetch permissions. Full MCP support, which includes actions that write, is limited to Business, Enterprise and Edu workspaces. There is no MCP on Plus, and none on the free tier.

On Pro you enable Developer mode in ChatGPT on the web, under Settings → Apps → Advanced settings; on accounts still showing the older naming the same toggle is at Settings → Connectors → Advanced. OpenAI's own instructions are in Developer mode and MCP apps in ChatGPT.

Then add a custom connector pointing at one of the access points above, and authenticate either with OAuth or with a bearer token.

Because Pro is read-and-fetch only, an Aigon connector there will read and search your notes but will not be able to write to them. If you want the full surface without a Business workspace, the REST access point is the way round it.

MCP CURL

Any LLM that has code execution capabilities can use the MCP REST API directly. In principle this API also allows for OAuth login, but in practice the LLM may not be able to execute the flow, so you may need to generate and use a bearer token. You can point your LLM to

mcp.aigon.ai/rest/openapi.json

for reading the API specifications — that is the machine-readable OpenAPI document.

In principle you can give it the bearer token directly, but this is not recommended because it will end up in its context, which is transmitted to your model provider. Instead, create a shell file secrets.sh that contains

export AIGON_BEARER_TOKEN=agatcf_74e403f441558f14b025288549f462

and tell your LLM to source it from there without looking at it. It can then use the variable without the value ever passing through its context:

source secrets.sh
curl -s -H "Authorization: Bearer $AIGON_BEARER_TOKEN" \
     https://mcp.aigon.ai/rest/whoami

Keep secrets.sh outside anything the LLM might read wholesale or commit — a token in a repository is a token in everyone's context.

Appendix

Bearer token

If you for some reason cannot authenticate via OAuth, for example because your LLM does not allow it, you can also create a bearer token that allows your LLM to access your account. Note however that this token is highly sensitive: everyone with this token has full access to your Aigon account so take the appropriate care when using it, and revoke it when it is no longer needed.

There is a single bearer token for your account that you can create using

/auth reset yes

The output will be something like

API Token Generated

•⁠  ⁠Token: agatcf_74e403f441558f14b025288549f462
•⁠  ⁠Generated: 2026-08-25 17:08 UTC

and the token is the string starting with agat.... You can clear your token using

/auth clear yes

which irrevocably removes this token. You need to create a new one using /auth reset yes and communicate it to your LLM in an appropriate manner.

The token is used in the standard manner, as an HTTP Authorization header on every request:

Authorization: Bearer agatcf_74e403f441558f14b025288549f462

That one header is all there is to it. It works the same way on all three access points, and the same slot accepts either credential — an OAuth access token or this API token — so a client that already speaks OAuth needs no special handling. A request without a usable token is answered with 401.

Most MCP clients have a field for a custom header when you add a server by URL; that is where this goes. For the REST access point you can equally pass it with curl -H.

No backwards compatibility

This API is designed for consumption with LLMs and just-in-time discovery, and it is subject to change without notice. Therefore do not write integrations that assume a certain input and output format as they will invariably break. Instead have the API interaction intermediated with an LLM and have it write ad-hoc code if needed.

Connection types

There are three access points for the Aigon MCP servers, using slightly different protocols. They are mostly interchangeable, but MCP technology is relatively recent, and different LLMs have different preference. Our suggestion is to try the three protocols in the order provided

(you may or may not have to add a \ at the end of the path, depending on your system). They all support logging in with OAuth against a1.aigon.ai, as well as bearer token authentication. We recommend always using OAuth and the bearer token fallback only if OAuth is not an option. For using OAuth, use the /weblogin or /wl command in WhatsApp to get a login link into a1.aigon.ai.

SSE and HTTP are the two MCP transports. Both speak the MCP protocol proper and expose the same functions; which one to use is purely a question of what your client supports. We recommend to use SSE if it is available.

What we call REST is an API that is semantically equivalent to the MCP server, so it is not technically following REST standards. Like a REST API it is operated with ordinary POST and GET / QUERY requests, so anything that can make an HTTP call can use it without speaking MCP at all. It carries its own OpenAPI description at mcp.aigon.ai/rest/docs.

CaSH model

The Aigon MCP design follows the CaSH specifications, which is optimised about progressive discovery and therefore extremely context-efficient. The core of the CaSH model is three functions only

Normally an LLM would be able to figure this out for themselves, but if they are stuck, ask them to look through the skills wether there is some information about how to solve a specific task. If you find there is not, please contact us and we'll gladly add it to our skills library.